Deep learning in forestry using uav-acquired rgb data: A practical review
Forests are the planet's main CO 2 filtering agent as well as important economical,
environmental and social assets. Climate change is exerting an increased stress, resulting …
environmental and social assets. Climate change is exerting an increased stress, resulting …
Review of wildfire modeling considering effects on land surfaces
Wildfires are part of the natural cycle of life in vegetated regions. The apparent increase in
size and frequency of recent years reflects land management legacy, expansion of human …
size and frequency of recent years reflects land management legacy, expansion of human …
[PDF][PDF] Agriculture, forestry and other land uses (AFOLU)
Executive Summary The Agriculture, Forestry and Other Land Use1 (AFOLU) sector
encompasses managed ecosystems and offers significant mitigation opportunities while …
encompasses managed ecosystems and offers significant mitigation opportunities while …
Global population exposure to landscape fire air pollution from 2000 to 2019
Wildfires are thought to be increasing in severity and frequency as a result of climate
change,,,–. Air pollution from landscape fires can negatively affect human health,–, but …
change,,,–. Air pollution from landscape fires can negatively affect human health,–, but …
Wildland fire detection and monitoring using a drone-collected RGB/IR image dataset
Current forest monitoring technologies including satellite remote sensing, manned/piloted
aircraft, and observation towers leave uncertainties about a wildfire's extent, behavior, and …
aircraft, and observation towers leave uncertainties about a wildfire's extent, behavior, and …
Multi-decadal trends and variability in burned area from the 5th version of the Global Fire Emissions Database (GFED5)
Long-term records of burned area are needed to understand wildfire dynamics, assess fire
impacts on ecosystems and air quality, and improve fire forecasts. Here we fuse multiple …
impacts on ecosystems and air quality, and improve fire forecasts. Here we fuse multiple …
Next day wildfire spread: A machine learning dataset to predict wildfire spreading from remote-sensing data
Predicting wildfire spread is critical for land management and disaster preparedness. To this
end, we present “Next Day Wildfire Spread,” a curated, large-scale, multivariate dataset of …
end, we present “Next Day Wildfire Spread,” a curated, large-scale, multivariate dataset of …
Machine-learning modelling of fire susceptibility in a forest-agriculture mosaic landscape of southern India
The recurrent forest fires have been a serious management concern in southern Western
Ghats, India. This study investigates the applicability of various geospatial data, machine …
Ghats, India. This study investigates the applicability of various geospatial data, machine …
A deep learning ensemble model for wildfire susceptibility mapping
A Bjånes, R De La Fuente, P Mena - Ecological Informatics, 2021 - Elsevier
Devastating wildfires have increased in frequency and intensity over the last few years,
worsened by climate change and prolonged droughts. Wildfire susceptibility mapping with …
worsened by climate change and prolonged droughts. Wildfire susceptibility mapping with …
Remote sensing of forest burnt area, burn severity, and post-fire recovery: A review
E Kurbanov, O Vorobev, S Lezhnin, J Sha, J Wang… - Remote Sensing, 2022 - mdpi.com
Wildland fires dramatically affect forest ecosystems, altering the loss of their biodiversity and
their sustainability. In addition, they have a strong impact on the global carbon balance and …
their sustainability. In addition, they have a strong impact on the global carbon balance and …